72 citations · 199 across the 12 of their papers we have counts for
12 papers
BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives
Sainan Liu, Shan Lin, Jingpei Lu +2
Implicit neural representations have become pivotal in robotic perception, enabling robots to comprehend 3D environments from 2D images. Given a set of camera poses and associated…
ORRN: An ODE-based Recursive Registration Network for Deformable Respiratory Motion Estimation with Lung 4DCT Images
Xiao Liang, Shan Lin, Fei Liu +2
Deformable Image Registration (DIR) plays a significant role in quantifying deformation in medical data. Recent Deep Learning methods have shown promising accuracy and speedup for…
SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation
Shan Lin, Yuheng Zhi, Michael C. Yip
Without ground truth supervision, self-supervised depth estimation can be trapped in a local minimum due to the gradient-locality issue of the photometric loss. In this paper, we p…
Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Identification, Reconstruction, and Tracking
Shan Lin, Albert J. Miao, Jingpei Lu +4
Accurate and robust tracking and reconstruction of the surgical scene is a critical enabling technology toward autonomous robotic surgery. Existing algorithms for 3D perception in…
Adversarial Pairwise Reverse Attention for Camera Performance Imbalance in Person Re-identification: New Dataset and Metrics
Eugene P. W. Ang, Shan Lin, Rahul Ahuja +2
Existing evaluation metrics for Person Re-Identification (Person ReID) models focus on system-wide performance. However, our studies reveal weaknesses due to the uneven data distri…
Reducing Annotating Load: Active Learning with Synthetic Images in Surgical Instrument Segmentation
Haonan Peng, Shan Lin, Daniel King +4
Accurate instrument segmentation in endoscopic vision of robot-assisted surgery is challenging due to reflection on the instruments and frequent contacts with tissue. Deep neural n…
Multi-Domain Adversarial Feature Generalization for Person Re-Identification
Shan Lin, Chang-Tsun Li, Alex C. Kot
With the assistance of sophisticated training methods applied to single labeled datasets, the performance of fully-supervised person re-identification (Person Re-ID) has been impro…
Multi-frame Feature Aggregation for Real-time Instrument Segmentation in Endoscopic Video
Shan Lin, Fangbo Qin, Haonan Peng +3
Deep learning-based methods have achieved promising results on surgical instrument segmentation. However, the high computation cost may limit the application of deep models to time…
LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images
Shan Lin, Fangbo Qin, Yangming Li +3
Intelligent vision is appealing in computer-assisted and robotic surgeries. Vision-based analysis with deep learning usually requires large labeled datasets, but manual data labeli…
Towards Better Surgical Instrument Segmentation in Endoscopic Vision: Multi-Angle Feature Aggregation and Contour Supervision
Fangbo Qin, Shan Lin, Yangming Li +3
Accurate and real-time surgical instrument segmentation is important in the endoscopic vision of robot-assisted surgery, and significant challenges are posed by frequent instrument…
Homogeneous Feature Transfer and Heterogeneous Location Fine-tuning for Cross-City Property Appraisal Framework
Yihan Guo, Shan Lin, Xiao Ma +2
Most existing real estate appraisal methods focus on building accuracy and reliable models from a given dataset but pay little attention to the extensibility of their trained model…
Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification
Shan Lin, Haoliang Li, Chang-Tsun Li +1
Most existing person re-identification (Re-ID) approaches follow a supervised learning framework, in which a large number of labelled matching pairs are required for training. Such…